Load packages

suppressWarnings(suppressMessages({
library(AUCell,quietly=T)
library(devtools,quietly=T)
library(tidyverse,quietly=T)
library(Seurat,quietly=T)
library(gridExtra,quietly=T)
library(gt,quietly=T)
library(glue,quietly=T)
library(scater,quietly=T)
library(tm,quietly=T)
library(gghalves,quietly=T)
library(broman,quietly=T)
library(viridis,quietly=T)
library(Cairo,quietly=T)
library(hrbrthemes,quietly=T)
library(ggplot2,quietly=T)
library(cowplot,quietly=T)
library(ggrepel,quietly=T)
library(plyr,quietly=T)
library(grid,quietly=T)
library(doRNG,quietly=T)
library(doSNOW,quietly=T)
library(mixtools,quietly=T)
library(SummarizedExperiment,quietly=T)
library(DT,quietly=T)
library(plotly,quietly=T)
library(NMF,quietly=T)
library(shiny,quietly=T)
library(rbokeh,quietly=T)
library(dynamicTreeCut,quietly=T)
library(R2HTML,quietly=T)
library(Rtsne,quietly=T)
library(zoo,quietly=T)
library(GSEABase,quietly=T)
library(magrittr, quietly=T)
library(imager, quietly=T)
library(EBImage, quietly=T)
library(STutility, quietly=T)
library(magrittr, quietly=T)
library(dplyr, quietly=T)
library(DT, quietly=T)
library(kableExtra, quietly=T)
library(ggpubr, quietly = T)
}))

same_umap_P2_P12_P22=readRDS("C:/Users/raine/OneDrive/Documents/BioInfo/newdataset/same_umap_P2_P12_P22.rds")
Idents (same_umap_P2_P12_P22) = "orig.ident"
P12 <- subset(same_umap_P2_P12_P22,idents = c("sdCLBNx1","sdCLBNx2"))

A

Fig4A: UMAP highlighting 3 qNSCs subclusters.

Idents(P12) = "Full_clusters"

qNSC3 = WhichCells(P12, idents = "P12_qNSC3")
qNSC1 = WhichCells(P12, idents = "P12_qNSC2")
qNSC2 = WhichCells(P12, idents = "P12_qNSC3")

DimPlot(P12, label = F,label.size = 4, pt.size = 1,repel=T,cols= c("#DEDEDE","#6F4D0F","#C59226","#EDC251","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE","#DEDEDE"))+NoLegend()

C

Fig4C: Dot plot analysis revealing that some TFs/TRs are enriched or exclusive to a specific cluster.

DefaultAssay(P12)="RNA"
my_levels <- c("P12_aNSC1","P12_aNSC2","P12_aNSC3","P12_aNSC4","P12_Astrocytes" ,"P12_Endothelial/Mural cells","P12_Ependymal cells","P12_GABAergic lineage","P12_GLUergic lineage","P12_Microglia","P12_Neuroblasts","P12_Oligos","P12_qNSC1","P12_qNSC3","P12_qNSC2", "P12_TAPs")
Idents(P12) <- factor(P12@active.ident,levels=my_levels)
suppressWarnings(suppressMessages(DotPlot(P12, features = c("Gsx2","Six3","Rorb","Eno1","Id4","Id3","Id2","Id1","Hopx","Fezf2","Dmrta2","Zic5","Tfap2c","Emx1"), idents = c("P12_qNSC1","P12_qNSC2","P12_qNSC3"), dot.scale = 10)+scale_colour_viridis(option="viridis")+theme_grey()+RotatedAxis()))

D

Fig4D: Spatial transcriptomic (Visium) showing the expression of Sox2 and Hopx.

se.cropped=readRDS("C:/Users/raine/OneDrive/Documents/visium/merge_se_cropped.rds")
Idents(se.cropped)="labels"
se.cropped <- RenameIdents(se.cropped,"svze18"="E17.5","svzp2"="P2","svzp12"="P12","svzp22"="P22")
se.cropped$labels <- Idents(se.cropped)
se.cropped@meta.data[["labels"]]=as.character(se.cropped@meta.data[["labels"]])
suppressMessages(suppressWarnings(se.cropped <- suppressMessages(se.cropped %>% 
  SCTransform(verbose = F) %>%
  RunPCA(verbose=F) %>%
  RunUMAP(reduction = "pca", dims = 1:20,verbose = F))))

FeatureOverlay(se.cropped, features = "Sox2",
sampleids = 1:4,
cols = c("light grey", "mistyrose", "darkred"),
pt.size = 3,
add.alpha = TRUE,
ncol = 4, show.sb = FALSE,
pt.alpha = 0.1,label.by = "labels")

FeatureOverlay(se.cropped, features = "Hopx",
sampleids = 1:4,
cols = c("light grey", "mistyrose", "darkred"),
pt.size = 3,
add.alpha = TRUE,
ncol = 4, show.sb = FALSE,
pt.alpha = 0.1,label.by = "labels")

M

Fig4M: Calculation of an AUCell score using best astrocytic markers defined by Zeisel et al., Cell, 2018.

my_comparisons <- list(c("P12_Astrocytes", "P12_qNSC1"), 
                       c("P12_Astrocytes", "P12_qNSC2"), 
                       c("P12_qNSC1", "P12_qNSC2"))

astro_quiescent <- c("P12_Astrocytes" = "#B882FC","P12_qNSC1" = "#75540D" , "P12_qNSC2"="#CB9B20")

suppressMessages(suppressWarnings(rankings10 %>%
  filter(class == "P12_qNSC1" |
          class == "P12_qNSC2" | 
      class == "P12_Astrocytes" ) %>%
  ggplot(aes(x = class, y = astroSets10,fill=class)) +
  geom_violin(trim = F,position = "dodge")+ggtitle("AUCell score astrocytes markers")+stat_compare_means(label="p.signif",comparisons = my_comparisons)+
  ylab("AUCell score")+theme_ipsum()+ scale_x_discrete("class", limits = c("P12_qNSC1", "P12_qNSC2","P12_Astrocytes"),labels=c("qNSC1","qNSC2","Astro"))+
  scale_fill_manual(values=astro_quiescent)+NoLegend()))